Vehicles and other machines with internal combustion engines, including diesel engines, gasoline engines, gaseous fuel-powered engines, and other engines, can produce a complex mixture of pollutants. These pollutants may include nitrogen oxides (NOx) and other compounds. Many machines are equipped with aftertreatment systems designed to reduce the amount of NOx and other pollutants that the machines release into the atmosphere. For example, some aftertreatment systems use selective catalytic reduction (SCR) to inject a gaseous or liquid reductant, such as urea, into an exhaust path to be absorbed into a substrate. Such a reductant may, in some examples, be known as Diesel Exhaust Fluid (DEF) in North America or as “Add-Blue” in Europe. The injected reductant can react with NOx in the exhaust path to form water and nitrogen. Conversion of NOx to water and nitrogen can accordingly reduce NOx levels actually emitted by the machine into the atmosphere.
Aftertreatment systems can include NOx sensors positioned in the exhaust path. The NOx sensors may, for example, be used to determine how much reductant to introduce into the exhaust path based on detected NOx levels. However, over time, measurements from a NOx sensor can drift away from actual NOx concentrations in emissions. Such measurement drift can indicate that a NOx sensor is failing, or has become faulty, even if conventional sensor diagnostics would not detect the issue. Inaccurate measurements from failing or faulty NOx sensors can lead to problems with a machine or its emissions. For example, inaccurate NOx measurements can cause an aftertreatment system to inject too much, or not enough, reductant into the exhaust path. Significant machine downtime and lost productivity can occur if failing NOx sensors are not detected and fixed. Accordingly, some methods have been developed to determine when emissions sensors have failed or are about to fail.
For example, U.S. Pat. No. 8,694,197 to Rajagopalan, (hereinafter “Rajagopalan”) describes a method of diagnosing vehicle NOx sensor faults. In particular, Rajagopalan can compare output received by a NOx sensor against fuel consumption over time, and determines a NOx sensor gain using a least-squares estimation for calculated means based on expected NOx sensor output. Rajagopalan can then determine if the NOx sensor gain is too high or too low relative to an expected output for the NOx sensor. However, the method described by Rajagopalan uses linear analysis to detect NOx sensor faults based on data associated with a single NOx sensor. The method of Rajagopalan also only begins when certain initial conditions are met, for instance when a rate of fuel flow to the engine is above a threshold to “help ensure that sufficient levels of NOx are present in the exhaust gas so as to result in an accurate diagnosis of NOx sensor faults.” Because Rajagopalan encourages analyzing NOx sensors only when relatively high NOx levels are present, Rajagopalan may be unable to detect failing NOx sensors when lower NOx levels are being produced, such as when the engine is idle and is consuming lower amounts of fuel.
The example systems and methods described herein are directed toward overcoming the one or more of the deficiencies described above.